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SUMMARY:Training course: Data assimilation
DTSTART;VALUE=DATE-TIME:20210510T074500Z
DTEND;VALUE=DATE-TIME:20210514T160000Z
DTSTAMP;VALUE=DATE-TIME:20201030T110826Z
UID:indico-event-208@events.ecmwf.int
DESCRIPTION:This five-day module focuses on describing data assimilation m
ethods and general aspects of assimilating observations. Aspects of the im
plementation of the assimilation techniques for real-size numerical weathe
r prediction (NWP) systems will also be described.\n\nAs well as lectures
there will be discussion and hands-on sessions - please see the draft time
table for more details.\n\nMain topics\n\n\n The fundamental data assimila
tion concepts\n Optimal Interpolation\, 3D-Var\, 4D-Var and the Kalman fil
ter\n Ensemble Kalman Filter methods\; Ensemble of Data Assimilations and
uncertainty estimation\; Hybrid variational/ensemble based methods\n Model
ling of error covariances\; handling of non-Gaussian errors\n The global o
bserving system\, with emphasis on how to use satellite observations\n Bia
s correction\, quality control and diagnostics\n Applications of data assi
milation methods for the land surface\, ocean\, atmospheric composition an
d reanalysis\n\n\nRequirements\n\nParticipants should have a good meteorol
ogical and mathematical background\, and in particular a good understandin
g of linear algebra. They are expected to be familiar with the contents of
standard meteorological and mathematical textbooks.\n\nIf you are less fa
miliar with data assimilation concepts\, such as Bayes Theorem\, you may w
ish to consider attending the University of Reading Introductory course\,
which runs the week before our course\; see details below.\n\nIntroductory
material not covered by the course can be found in our lecture note serie
s.\n\nSome practical experience in numerical weather prediction is an adva
ntage.\n\nAll lectures will be given in English.\n\nhttps://events.ecmwf.i
nt/event/208/
LOCATION:ECMWF
URL:https://events.ecmwf.int/event/208/
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